AI Researcher and New Rochelle Native Professor Zachary Lipton

“Elon Musk doesn’t really deserve to have a voice in the public discourse about machine learning. He’s not an expert…”
Zachary LIpton

Professor Zachary Lipton, Assistant Professor in the Tepper School of Business at Carnegie Mellon University.

Professor Zachary Lipton is an Assistant Professor in the Tepper School of Business at Carnegie Mellon University, with an appointment in the Machine Learning Department. He recently completed four years of PhD studies at UC San Diego’s Artificial Intelligence Group.
His research interests are eclectic, spanning both methods, applications, and social impacts of machine learning (ML), there exist a few notable clusters. He is especially interested in modeling temporal dynamics and sequential structure in healthcare data, e.g., Learning to Diagnose. Additionally, he works on critical questions related to how we use ML in the wild, yielding The Mythos of Model Interpretability, and more recent work on the desirability and reconcilability of various statistical interpretations of fairness.
He is a native of New Rochelle, New York, attended Columbia University as an undergraduate, and is a jazz saxophonist.

Artificial Intelligence, Machine Learning, and Deep Learning

Terrance Jackson: What is the difference between artificial intelligence, machine learning, and deep learning?
Zachary Lipton: From the crazy way these topics are covered in the media, it can be hard to tell the meanings of the various terms. Often they are compared to each other, e.g. what deep learning can do vs what machine learning can do. The most faithful, simple way to put it is that they have a subset relationship. AI was a field long before people were interested in machine learning. It encompasses the study of how to do, with machines, all things that we think requires something like human intelligence. Of course that makes it a bit of a moving target. Once we know how to do something well, such as playing chess, then we sometimes don’t subsequently view it as a critical piece of AI.

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Interview with Trevor Koverko, CEO of Polymath

Security tokens will dominate the blockchain universe!
Trevor Koverko

Trevor Koverko, CEO of Polymath

Trevor Koverko is prominent blockchain founder, investor and speaker.
After launching his career at the convergence of Wall Street and Silicon Valley, Trevor became a very early leader in the blockchain community.
Trevor started in 2012 in Bitcoin, has keynoted major blockchain events like The North American Bitcoin Conference, and seeded foundation projects like Ethereum, Aion, QTum, Hive, EOS, and Shapeshift.
In 2017, after predicting the mega-trend of financial securities migrating to the blockchain, Trevor cofounded Polymath – the worlds largest securities token network.
Trevor graduated from Canada’s leading business school, Ivey, was a NHL draft pick of the New York Rangers and is a 4x attendee of Satoshi Roundtable.

Polymath logo

Terrance Jackson: What is Polymath?
Trevor Koverko: I founded Polymath in 2017 after wanting to launch a token of my own for a company I founded.
I quickly learned that the token I wanted to launch would actually be considered a security token — a token that would represent shares in my company. I also learned that the barrier to entry when it came to creating a security token was simply too high for many companies.
That’s when I had the idea for Polymath and to disrupt the legacy securities industry. Polymath, which is an open-source platform, gives issuers of financial products access to the blockchain, smart contracts, and token creation technology.
Polymath provides a protocol to ease issuers– such as venture capital firms, investment funds, and companies– through the complex tech and legal processes of a successful security token launch.
In short, the idea behind Polymath is an interface between financial securities and the blockchain.

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Can Google Predict the Stock Market

Can Google Predict the Stock Market
Using Artificial Intelligence to Analyze Financial Data
A Machine Learning Demonstration by
Terrance Jackson
Monday, May 21 @ 7 pm
Larchmont Public Library
121 Larchmont Avenue, Larchmont, NY
Can we use artificial intelligence and machine learning techniques on information collected by companies such as Google, Facebook, Wikipedia, and Twitter to help predict financial markets?


Based on the research of Tobias Preis, a professor of Behavioural Science & Finance at the Warwick Business School, using a trading strategy based on the changes of how often people Googled the word “debt,” yielded a return of 326% for the Dow Jones Industrial Average (DJIA). This is compared to a 16% return for a buy and hold strategy.

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Genius Farm: Closing the Achievement Gap

Genius Farm

We must educate our children for the 21st Century
When it comes to technology skills, the U.S. comes in last place — right below Poland. In addition, there was a significant racial difference with non-whites scoring below whites.
That’s why we are introducing students to artificial intelligence (A.I.), computer vision, data science, machine learning, robotics and blockchain technology.
Tech’s biggest companies are placing huge bets on artificial intelligence (A.I.) where typical A.I. specialists can be paid from $300,000 to $500,000 a year or more in salary and company stock.
The Achievement Gap
For decades, educators have struggled to close the “achievement gap,” the persistent differences in test scores, grades and graduation rates among students of different races, ethnicities and, in some subjects, genders.
According to an American Psychological Association article, a group of social and cognitive psychologists have approach this problem not based on the idea that at least some of these disparities are the result of faulty teaching or broken school systems, but instead spring from toxic stereotypes that cause ethnic-minority and other students such as women to question whether they belong in school and whether they can do well there. While such a major problem might seem to require widespread social change to fix, the psychologists are finding evidence that short, simple interventions can make a surprisingly large difference.
In a Scientific American article “Time to Raise the Profile of Women and Minorities in Science” written by Brian Welle and Megan Smith of Google, we learn:
Google recently commissioned a project to identify what makes girls pursue education in computer science. The findings reinforced what we already knew. Encouragement from a parent or teacher is essential for them to appreciate their own abilities. They need to understand the work itself and see its impact and importance. They need exposure to the field by having a chance to give it a shot. And, most important, they need to understand that opportunities await them in the technical industry.
It took some time, but Google realized that it recognized zero women with their Google Doodles, the embellishments of their corporate logo on their home page. Little things like this can have big impacts and to change the situation we need to look beyond the individual. As Malcolm Gladwell wrote in Outliers which The New York Times printed the first chapter:
[Y]ou couldn’t understand why someone was healthy if all you did was think about their individual choices or actions in isolation. You had to look beyond the individual. You had to understand what culture they were a part of, and who their friends and families were, and what town in Italy their family came from. You had to appreciate the idea that community — the values of the world we inhabit and the people we surround ourselves with — has a profound effect on who we are. The value of an outlier was that it forced you to look a little harder and dig little deeper than you normally would to make sense of the world. And if you did, you could learn something from the outlier that could use to help everyone else.
In Outliers, I want to do for our understanding of success what Stewart Wolf did for our understanding of health.

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Emin Gün Sirer: Bitcoin is Still Broken

Emin Gün Sirer

Emin Gün Sirer is a computer science professor at Cornell University. His research spans operating systems, networking, and distributed systems. He’s also co-director of the Initiative for Cryptocurrencies & Contracts, which is an initiative of faculty members at Cornell University, Cornell Tech, UC Berkeley, UIUC and the Technion to help to advance the adoption of cryptocurrencies and smart contracts.
In 2002, he started Karma, an early cryptocurrency that was the first to utilize a proof-of-work concept. He has written several influential white papers and blog posts (on Hacking Distributed) that have altered the course of Ethereum’s development. He was among the first to warn about the vulnerabilities that led to the collapse of The DAO. He also acts as the Blockchain Advisor for the WeTrust project.
He is currently number 29 on the list of the Most Influential Blockchain People.

Most Influential Blockchain People

Terrance Jackson: In 2013, You and Ittay Eyal wrote “Bitcoin is Broken.” Is Bitcoin still broken?
Emin Gün Sirer: Indeed, we found the biggest known fundamental weakness in Satoshi Nakamoto’s consensus protocol, known as Selfish Mining. Using our strategy, one can subvert Satoshi’s protocol, and possibly make more money than their fair share, at the cost of disrupting the system’s behavior. Luckily, we provided a fix for selfish mining attacks for miners smaller than 25%, but the threat from large miners is always going to be present.
Now that the attack is well-known, the community knows how to detect such attacks and put pressure on the actors who launch them. In fact, if anything, the community is hyper-diligent against miners that are too big, and puts pressure on them to break them up. No Bitcoin miner is big enough to unilaterally go selfish and harm the system.
The situation is quite different in other cryptocurrencies, however. Selfish Mining could be employed against other smaller coins.

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I Could Be… a documentary addressing inequity

I Could Be... A Documentary

I could be a congresswoman
Or a garbage woman or
Police officer, or a carpenter
I could be a doctor and a lawyer and a mother
And a good God woman what you’ve done to me
Kind of lover I could be
I could be a computer analyst
The Queen with the nappy hair raising her fist
Or I could be much more and a myriad of this
Hot as the summer, sweet as the first kiss
And even though I can do all these things…
~ Jill Scott
The Fact Is (I Need You)

Nassim Taleb

Nassim Taleb, author of The Black Swan and Antifragile, wrote in a Forbes article called “You Can’t Predict Who Will Change The World:“
“It is high time to recognize that we humans are far better at doing than understanding, and better at tinkering than inventing. But we don’t know it. We truly live under the illusion of order believing that planning and forecasting are possible. We are scared of the random, yet we live from its fruits.”

Billionaire chess

Want Your Children to Succeed?

Raspberry Turk

We are organizing a group of students to build a robot that can play chess on the Ethereum Blockchain. This project will introduce our students to computer vision, data science, machine learning, robotics and blockchain technology. The design will be based on Joey Meyer’s Raspbery Turk and a Chess game for Ethereum from the Technical University of Berlin.

Zaleik Walsh and Julian Harris programming the Raspberry Pi for the chess-playing robot.

“In the past,” says Andrew Ng, the former chief scientist at Baidu Research and founder of the “Google Brain” project, “a lot of S&P 500 CEOs wished they had started thinking sooner than they did about their Internet strategy. I think five years from now there will be a number of S&P 500 CEOs that will wish they’d started thinking earlier about their AI strategy.”

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Blockchain to Reverse Climate Change & Diabetes

We are researching Blockchain applications for Urban Agriculture.
“Food is key to nearly everything,” solutions for food production will actually come from cities, and blockchain technology will be critical in developing those solutions.
[T]he issues that confront most Americans directly are income, food (thereby, agriculture), health and climate change. (And, of course, war, but let’s leave that aside for now.)

Mark Bittman

These are all related: You can’t address climate change without fixing agriculture, you can’t fix health without improving diet, you can’t improve diet without addressing income, and so on. The production, marketing and consumption of food is key to nearly everything. (It’s one of the keys to war, too, because large-scale agriculture is dependent on control of global land, oil, minerals and water.)

Jane Jacobs - The Economy of Cities

“Food is key to nearly everything” and the solutions for food production will actually come from cities. As Jane Jacobs wrote in The Economy of Cities:
Current theory in many fields—economics, history, anthropology—assumes that cities are built upon a rural economic base. If my observations and reasoning are correct, the reverse is true: that is, rural economics, including agricultural work, are directly built upon city economics and city work.
Jacobs theorized that cities predated agriculture. She is probably wrong on that particular premise, but she was pointing to a deeper truth, as a Planetizen article notes:
[D]espite the “total fallacy” of Jacobs’s statement that cities came first, she had a valid point when she stated that agricultural development benefited from urban stimuli. Monica Smith also notes that the Cities First model “requires modifications but still contains an element of truth in that cities provide significant boosts to rural productivity” by promoting certain efficiencies of cultivation….
I support… the archaeological consensus on the relationship between agriculture and urban origins. At best, agriculture and cities evolved hand-in-hand in what Soja describes as a “mutually causal and symbiotic relationship.” But perhaps there’s still something to the idea of Cities First if we focus on cities not as things (or, products) but as processes.
Solutions for food production will come from cities, and blockchain technology will be critical in developing those solutions.
Blockchain technology came to popular notice with the rise of bitcoin and other cryptocurrencies. The technology allows for highly secure digital transactions and recordkeeping. Even though blockchain found its first use in cryptocurrencies, the concept can be applied to all sorts of transactions, including agricultural ones.

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